Wireless communications techniques are now widely used in a variety of applications, including mobile (e.g., cellular) radiotelephones, paging systems, personal communications systems (PCS) and the like. As the demands of these applications have increased, an ever-present challenge to the implementation of wireless applications has been the need to develop improved signal processing techniques to expand the information capacity of wireless links and to improve the quality and reliability of information transfer over these wireless links.
One of the greatest challenges in wireless communications is compensating for environmentally-induced signal distortions such as fading and interference. Referring to FIG. 1, a radio communications channel 20 connects a transmitting station 10 and a receiving station 30. Components of the channel 20 can affect communications between the stations 10, 30, and include the communications medium, e.g., the atmospheric signal path across which radio communications signals are transmitted and which may introduce fading and interference into the radio communications signals. Fading may include long-term fading due to variations in terrain along the signal propagation path, as well as short-term multipath fading due to reflections from features such as buildings which cause fluctuations in received signal strength and other distortions at a receiving station. Mobile terrestrial radio communications are particularly susceptible to short-term multipath fading because the signal pathways tend to be close to the ground. Other elements which may have an effect on communications include transmitting and receiving components such as transmitters, receivers and antennas.
Various signal processing techniques are conventionally employed to deal with signal degradation over a channel, including diversity reception, signal coding, and specialized modulation/demodulation techniques which utilize estimates of a channel transfer characteristic for the channel. Diversity reception techniques included spatial diversity reception using multiple spaced-apart receiving antennas, and polarization diversity reception using multiple antennas designed to accept electromagnetic signals having particular polarizations. Typical signal coding schemes apply redundancy to enhance the accuracy of an estimate produced from a received signal. Channel estimation techniques such as pilot tone or symbol assisted modulation and demodulation can provide improved knowledge of a transfer characteristic for the channel to aid in estimating information from a received signal. The modulation/demodulation scheme implemented in the transmitting station 10 and the receiving station 30 can also influence the performance of the radiotelephone communications channel 20. Although a modulation scheme alone can provide better performance in a fading environment, conventional systems may employ a combination of coding and modulation to provide improved performance.
A commonly used combination of coding and modulation employs convolutional coding with a quadrature amplitude modulation (QAM) scheme such as 16-QAM. A source bit stream is input into a convolutional coder which produces a coded bit stream. This coded bit stream is then used to generate a communications signal by a QAM modulator which maps groups of the coded bits to signals selected from a set of signals of various amplitude and phase. The modulated signal is communicated over a communications medium to a receiving station. The received signal is demodulated by a demodulator to produce an information stream which is subsequently decoded in a convolutional decoder. To improve coding performance, it is generally desirable that the information stream produced by the demodulator is so-called "soft information," e.g., an indication of a relative probability that a bit in the source bit stream has a particular value.
Techniques for producing such soft information from a demodulator have been proposed which involve computation of a log likelihood ratio that represents a ratio of the probability that a particular bit has a "1" value to the probability that the bit has a value of "0." For example, Le Goffet al., "Turbo-Codes and High Spectral Efficiency Modulation", ICC '94 Conf. Rec., pp. 645-649, have proposed a simplified approach to computation of such log likelihood ratios using approximations based on signal-to-noise ratio (SNR) and channel characteristics, while Zehavi, "8-PSK Trellis Codes for a Rayleigh Channel," IEEE Trans. Commun., vol. 40, no. 5, May 1992, pp. 873-884, has proposed a trellis-coded modulation scheme in which soft information is computed using simplified path metrics. Unfortunately, the approximations of the former approach are based on questionable assumptions, while the latter approach generally requires a computation of an extensive set of path metrics which may pose an undesirable computational burden.